Paternalistic Interventions: Determinants of Demand and Supply

Last registered on February 16, 2024
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Pre-Trial

Trial Information

General Information

Title
Paternalistic Interventions: Determinants of Demand and Supply
RCT ID
AEARCTR-0007108
Initial registration date
February 16, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 16, 2024, 4:33 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
United States of America
Region

Primary Investigator

Name
Krishna Srinivasan
Affiliation
University of Zurich
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Bjoern Bartling
PI Affiliation
University of Zurich
Contact Investigator

Additional Trial Information

Status
In development
Start date
2024-02-21
End date
2025-02-21
Keywords
Behavior, Governance, Welfare
Additional Keywords
Paternalism; paternalistic interventions
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Interventions by governments, experts, and parents in the lives of others are commonly motivated by a desire to help. What factors influence individuals’ willingness to intervene in the decisions made by others? What factors influence individuals’ attitudes toward paternalistic interventions imposed upon them? We conduct an experiment in a general population sample of the U.S. to address these questions.
External Link(s)

Registration Citation

Citation
Bartling, Bjoern and Krishna Srinivasan. 2024. "Paternalistic Interventions: Determinants of Demand and Supply." AEA RCT Registry. February 16. https://doi.org/10.1257/rct.7108-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-02-21
Intervention End Date
2025-02-21

Primary Outcomes

Primary Outcomes (end points)
Key outcome for Choosers: Fraction of Choosers demanding an intervention. Key outcome for Choice Architects: Fraction of Choice Architects supplying an intervention. See the pre-analysis plan for more details.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomly assign study participants to either the role of a “Chooser” or a “Choice Architect.” Each Chooser is randomly paired with a Choice Architect. The Chooser is tasked with selecting between two bonus options. To introduce potential decision-making errors, one bonus option is presented transparently, while the other bonus option is obscured, increasing the likelihood of the Chooser selecting the lower bonus. The Choice Architect has the opportunity to intervene in the Chooser’s decision to assist them in securing the higher bonus. We randomize study participants into one of six treatments in a 3 x 2 design. See the pre-analysis plan for more details.
Experimental Design Details
Not available
Randomization Method
Software-based randomization (Qualtrics)
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1
Sample size: planned number of observations
4000 participants in the role of Choosers and 4000 participants in the role of Choice Architects.
Sample size (or number of clusters) by treatment arms
500 pairs of participants in the Soft x No Info and Hard x No Info treatments and 750 pairs in each of the other four treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The Minimum Detectable Effect Sizes regarding our main hypotheses range from 5.1 to 8.9 percentage points. See the pre-analysis plan for more details.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The Human Subjects Committee of the Faculty of Economics, Business Administration and Information Technology at the University of Zurich
IRB Approval Date
2022-09-01
IRB Approval Number
2022-069
Analysis Plan

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